Abstract
Cloud computing is considered to be energy and ecological efficient, and is promoted as the environmental friendly computing solution. On the other hand, the massive development of the Cloud marketplace lead in an increase of the Data Centers globally and eventually in the increase of the CO2 related footprint. The calculation of the impact of Virtual Machines (VMs) on the environment is a challenging task, not only due to the technical difficulties but also due to the lack of information from the energy providers. In this paper we present a methodology for the estimation of the ecological efficiency of Virtual Machines in Cloud infrastructures. We focus on the information management in relation with the energy production in a region as well as the ecological efficiency of a VM in a Data Center. To this end, we have designed and implemented a framework through which the ecological efficiency can be monitored. The presented framework is being evaluated through a private Cloud scenario deployed into infrastructure located in Germany.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Gartner: Gartner Report for ICT Industry (2009), http://www.gartner.com/it/page.jsp?id=503867
Dirks, S., Gurdgiev, C.: The emergence of the eco-efficient economy. Technical report, IBM (2010)
Berl, A., Gelenbe, E., Di Girolamo, M., Giuliani, G., De Meer, H., Dang, M.Q., Pentikousis, K.: Energy-efficient cloud computing. The Computer Journal 53(7), 1045–1051 (2010)
Greenberg, A., Hamilton, J., Maltz, D.A., Patel, P.: The cost of a cloud: Research problems in data center networks. SIGCOMM Comput. Commun. Rev. 39(1), 68–73 (2008)
Chen, Q., Grosso, P., Veldt, K.V.D., Laat, C.D., Hofman, R., Bal, H.: Profiling Energy Consumption of VMs for Green Cloud Computing. In: 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing, pp. 768–775 (December 2011)
Kansal, A., Zhao, F., Bhattacharya, A.A.: Virtual Machine Power Metering and Provisioning. In: Proceedings of the 1st ACM Symposium on Cloud Computing, pp. 39–50 (2010)
Stoess, J., Lang, C., Bellosa, F.: Energy Management for Hypervisor-Based Virtual Machines (2007)
Husain Bohra, A.E., Chaudhary, V.: VMeter: Power modelling for virtualized clouds. In: 2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW), pp. 1–8 (April 2010)
Basmadjian, R., Ali, N., Niedermeier, F., de Meer, H., Giuliani, G.: A methodology to predict the power consumption of servers in data centres. In: Proceedings of the 2nd International Conference on Energy-Efficient Computing and Networking, e-Energy 2011, pp. 1–10. ACM, New York (2011)
Katsaros, G., Subirats, J., Fitó, J.O., Guitart, J., Gilet, P., Espling, D.: A service framework for energy-aware monitoring and VM management in Clouds. Future Generation Computer Systems (December 2012)
Vandierendonck, H., De Bosschere, K.: Many benchmarks stress the same bottlenecks. In: Workshop on Computer Architecture Evaluation Using Commercial Workloads, pp. 57–64 (2004)
Phansalkar, A., Joshi, A., Eeckhout, L., John, L.: Measuring program similarity: Experiments with SPEC CPU benchmark suites. In: 2005 IEEE International Symposium on Performance Analysis of Systems and Software, pp. 10–20 (2005)
Quang-Hung, N., Nien, P.D., Nam, N.H., Huynh Tuong, N., Thoai, N.: A genetic algorithm for power-aware virtual machine allocation in private cloud. In: Mustofa, K., Neuhold, E.J., Tjoa, A.M., Weippl, E., You, I. (eds.) ICT-EurAsia 2013. LNCS, vol. 7804, pp. 183–191. Springer, Heidelberg (2013)
Beloglazov, A., Abawajy, J., Buyya, R.: Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing. Future Generation Computer Systems 28(5), 755–768 (2012)
Hsu, C.H., Chen, S.C., Lee, C.C., Chang, H.Y., Lai, K.C., Li, K.C., Rong, C.: Energy-Aware Task Consolidation Technique for Cloud Computing. In: CLOUDCOM 2011: Proceedings of the 2011 IEEE Third International Conference on Cloud Computing Technology and Science. IEEE Computer Society (November 2011)
Lin, C., Liu, P., Wu, J.: Energy-efficient virtual machine provision algorithms for cloud systems, 81–88 (2011)
Google: Google Green Products (March 2013), http://www.google.com/green/bigpicture
Curry, E., Hasan, S., White, M., Melvin, H.: An Environmental Chargeback for Data Center and Cloud Computing Consumers (April 2012)
Moghaddam, F., Cheriet, M., Nguyen, K.K.: Low carbon virtual private clouds. In: 2011 IEEE International Conference on Cloud Computing (CLOUD), pp. 259–266 (2011)
Gao, P.X., Curtis, A.R., Wong, B., Keshav, S.: It’s not easy being green. In: Proceedings of the ACM SIGCOMM 2012 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication, SIGCOMM 2012, pp. 211–222. ACM, New York (2012)
Garg, S.K., Yeo, C.S., Buyya, R.: Green cloud framework for improving carbon efficiency of clouds. In: Jeannot, E., Namyst, R., Roman, J. (eds.) Euro-Par 2011, Part I. LNCS, vol. 6852, pp. 491–502. Springer, Heidelberg (2011)
Greenpeace: Campain Report, How Clean is Your Cloud (2012), http://www.greenpeace.org/international/en/publications/Campaign-reports/Climate-Reports/How-Clean-is-Your-Cloud/
Wagner, H.J., Koch, M., Burkhardt, J., Böckmann, T., Feck, N., Kruse, P.: CO 2 -Emissionen der Stromerzeugung. BWK 59(10), 44–52 (2007)
Lübbert, D.: CO 2 -Bilanzen verschiedener Energieträger im Vergleich. Technical report (2007)
Zhang, Z., Fu, S.: Profiling and analysis of power consumption for virtualized systems and applications. In: 2010 IEEE 29th International Performance Computing and Communications Conference (IPCCC), pp. 329–330 (2010)
Viswanathan, H., Lee, E.K., Rodero, I., Pompili, D., Parashar, M., Gamell, M.: Energy-aware application-centric vm allocation for hpc workloads. In: 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW), pp. 890–897 (2011)
Chen, Q., Grosso, P., van der Veldt, K., de Laat, C., Hofman, R., Bal, H.: Profiling energy consumption of vms for green cloud computing. In: 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing (DASC), pp. 768–775 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Katsaros, G., Stichler, P. (2013). Quantifying Ecological Efficiency in Cloud Computing. In: Altmann, J., Vanmechelen, K., Rana, O.F. (eds) Economics of Grids, Clouds, Systems, and Services. GECON 2013. Lecture Notes in Computer Science, vol 8193. Springer, Cham. https://doi.org/10.1007/978-3-319-02414-1_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-02414-1_6
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02413-4
Online ISBN: 978-3-319-02414-1
eBook Packages: Computer ScienceComputer Science (R0)